Voyage performance varies even between seemingly identical ships, and models built on vessel-type averages often miss the mark. Manta Marine Technologies (Manta) closes that gap with machine learning (ML) models trained on each vessel’s own operational history. In this post, we show how Manta delivers vessel-specific voyage optimization with machine learning on Amazon Web Services (AWS), helping shipowners reduce fuel consumption and improve voyage efficiency.
Differences in hull condition, trim, draft, machinery condition, loading patterns, and operational practices mean that when operators build models on vessel-type averages, those models often can’t capture how a specific vessel performs. For shipowners, this gap translates directly into unnecessary fuel consumption and cost.
Manta takes a vessel-specific approach. The company trains machine learning models on each vessel’s own operational history and combines them with forecast weather and ocean…
